Modeling the spatio‑temporal spread of COVID‑19 cases, recoveries and deaths and effects of partial and full vaccination coverage in Canada | Scientific Reports

Nature·Oct 24

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Researchers have developed models to predict the spread of COVID-19, taking into account spatial and temporal factors. These models, which have been applied to various regions including Canada, England, the US, Spain, and Poland, aim to forecast the spread of the disease and assess the impact of factors such as vaccination coverage and mobility. The approaches used to develop these models include spatio-temporal neural networks, Bayesian models, and multiagent modeling.

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